The PLM Procedure

The LSMESTIMATE statement provides a mechanism for obtaining custom hypothesis tests among least squares means.

Table 8 summarizes the options available in the LSMESTIMATE statement.

Table 8: LSMESTIMATE Statement Options

Option	Description
Construction and Computation of LS-Means
AT	Modifies covariate values in computing LS-means
BYLEVEL	Computes separate margins
DIVISOR=	Specifies a list of values to divide the coefficients
OM=	Specifies the weighting scheme for LS-means computation as determined by a data set
SINGULAR=	Tunes estimability checking
Degrees of Freedom and p-Values
ADJUST=	Determines the method of multiple-comparison adjustment of LS-means differences
ALPHA=	Determines the confidence level ()
LOWER	Performs one-sided, lower-tailed inference
STEPDOWN	Adjusts multiple-comparison p-values further in a step-down fashion
TESTVALUE=	Specifies values under the null hypothesis for tests
UPPER	Performs one-sided, upper-tailed inference
Statistical Output
CL	Constructs confidence limits for means and mean differences
CORR	Displays the correlation matrix of LS-means
COV	Displays the covariance matrix of LS-means
E	Prints the matrix
ELSM	Prints the matrix
JOINT	Produces a joint F or chi-square test for the LS-means and LS-means differences
PLOTS=	Produces graphs of means and mean comparisons
SEED=	Specifies the seed for computations that depend on random numbers
Generalized Linear Modeling
CATEGORY=	Specifies how to construct estimable functions for multinomial data
EXP	Exponentiates and displays LS-means estimates
ILINK	Computes and displays estimates and standard errors of LS-means (but not differences) on the inverse linked scale

For more information about the syntax of the LSMESTIMATE statement, see the section LSMESTIMATE Statement in Chapter 20, Shared Concepts and Topics.